70 citations · 293 across the 70 of their papers we have counts for
6 papers · 1 filter
Obfuscation via Information Density Estimation
Hsiang Hsu, Shahab Asoodeh, Flavio du Pin Calmon
Identifying features that leak information about sensitive attributes is a key challenge in the design of information obfuscation mechanisms. In this paper, we propose a framework…
Predictive Multiplicity in Classification
Charles T. Marx, Flavio du Pin Calmon, Berk Ustun
Prediction problems often admit competing models that perform almost equally well. This effect challenges key assumptions in machine learning when competing models assign conflicti…
Optimized Score Transformation for Consistent Fair Classification
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flavio du Pin Calmon
This paper considers fair probabilistic binary classification where the outputs of primary interest are predicted probabilities, commonly referred to as scores. We formulate the pr…
Correspondence Analysis Using Neural Networks
Hsiang Hsu, Salman Salamatian, Flavio P. Calmon
Correspondence analysis (CA) is a multivariate statistical tool used to visualize and interpret data dependencies. CA has found applications in fields ranging from epidemiology to…
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
Hao Wang, Berk Ustun, Flavio P. Calmon
When the performance of a machine learning model varies over groups defined by sensitive attributes (e.g., gender or ethnicity), the performance disparity can be expressed in terms…
Robustness of Maximal -Leakage to Side Information
Jiachun Liao, Lalitha Sankar, Oliver Kosut +1
Maximal -leakage is a tunable measure of information leakage based on the accuracy of guessing an arbitrary function of private data based on public data. The parameter dete…